Systems for intelligent vehicles range from manual (i.e. a human driver is involved and a robot driver is not) to autonomous (i.e. a robot driver is involved and a human driver is not). For example, a system that navigates a Tesla garbage truck must perform essential tasks such as minimizing fuel consumption and carbon emissions, while keeping a distance from pedestrians, cyclists, and cars. Such a system must also make decisions in the face of ethical dilemmas such as those that occur in the trolley problem.

In this course, BUA students will put their hands on developing such systems that are robust to potential dilemmas as much as possible. During the course, they will get to design and assess algorithms for reference maps and object detection. Course prerequisites are skills in mathematics, programming (e.g. Python, C, Java, C++), statistics (e.g. mean, standard deviation), or ethics. Course activities include normally individual supervision, team tasks, invited talks, and conference participation.